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Introduction¶

Unemployment remains one of the most daunting challenges facing African nations today. It is a multifaceted problem with deep roots in socio-economic, educational, and policy-related factors. This case study invites analysts and policymakers to delve into various datasets to uncover insights and strategies that could assist in mitigating the unemployment crisis in Africa.

Objective¶

The primary goal of this case study is to analyze data, identify patterns, and propose informed, data-driven recommendations that governments and stakeholders can implement to effectively address and reduce unemployment rates, particularly focusing on the African context.

Data Overview¶

Participants will engage with six diverse datasets, each offering a unique perspective on factors influencing unemployment:

  1. Unemployment Rate (Men vs. Women): This dataset provides a comparative view of unemployment rates between genders.
  2. National Strategy for Youth Employment: This dataset outlines various national strategies adopted across different African countries to combat youth unemployment.
  3. Share of Education in Government Expenditure: Education is a critical factor in employment. This dataset sheds light on how much governments are investing in education.
  4. Population with Access to Electricity: Access to electricity is a fundamental driver of economic development and can influence employment opportunities. This dataset provides insights into the availability of electricity across different regions and its potential impact on employment.
  5. Total Firms (Historical Data): The health of a country's private sector is directly linked to employment rates. This dataset includes historical data on the number of firms.
  6. Country Codes: This dataset is essential for mapping data points to specific African countries, enabling a more precise and geographically contextual analysis.

Nigeria's population growth over time¶

A significant spike in population growth is seen in nigeria from the 20000 and eventually surpassing the 200 million population.

Nigeria's Unemployment rate since 1990¶

Unemployment rate among Nigerians have been quiet low throughout the 90's as well as the early 20's. A spike was recorded from 2013 and it has been on the rise since.

Government Expenditure on education¶

Expenditure on education has been on the decline over the past 5 years and this is a worrying trend. Education plays a critical role in the development and growth of any nation and as seen in prior chart as population increases, expenditure in education should not be on the decrease but increase to cater to the needs of the growing population.

Access to electricity¶

A steady increase in the percentage of the population with access to electricity is noted in the chart above. Although a desired 100% is still off, progress is gradually being recorded.

Number of Limited Liability companies¶

A steady increase in the number of registered LLC is seen in the country. The number have almost doubled over the course of the last decade going from around 800k to 1.6M from 2010 to 2020.

National Strategy for Youth Employment¶

For a long period of time, Nigeria haven't operated a developed national strategy for youth employment. All these change in 2019 when the nation launched 2 strategy.

Correlation heatmap¶

The heatmap above shows the relationship between all the indicators in the data. As expected there is a high positive correlation between unemployment in both male and female with population, number of LLC's and dusiness density ration. A mild correlation is noted between unemployment and electricity while a large negative correlation is seen between unemployment and government expendeiture on education. This goes on to show that as the amount spend on education increases, unemployment tends to decrease.

Relationship between Unemployment and expenditure on education¶

As expected, the data shows a negative relationship where unemployment reduces as the percentage of expenditure dedicated to education increases. This hold true for both male and female population.

Predictive model for estimating the impact of increase in education expenditure on unemployment¶

The linear regression model above is represented by the equation

\begin{equation} y = 0.03247930391540247x_1 - 0.4969933374998647x_2 + 9.968270789033804 \end{equation}

For every 1% increase in female unemployment, government expenditure on education is expected to increase by 0.0325%.

For every 1% increase in male unemployment, government expenditure on education is expected to decrease by 0.497%.

The intercept (9.97) represents the baseline education expenditure with zero unemployment.

Relationship between Electricity access and Unemployment¶

The relationship shows a mild correlation between the two indicators.

Business density vs Unemployment¶

Strong relationship noted between business density and total unemployment as expected.

Business density rate forecast¶

Forecast shows that the value of Total business density rate is expected to continue its upward trajectory. This trends needs to be supported and the slope made steeper if possible to provide more employment for the growing population.

Unemployment in Africa¶

South Africa and Dibouti top the unemployment chart in Africa.

Recommendations¶

  • Policymakers should consider the following adjustments in response to the predictive model findings findings:

    • For each 1% increase in female unemployment, allocate an additional 0.0325% to government expenditure on education.
    • Conversely, for each 1% increase in male unemployment, consider a reduction of 0.497% in education spending.
    • The baseline education expenditure, represented by the intercept (9.97), should guide budgetary decisions in the absence of unemployment.
  • The presence of electricity is generally associated with an average correlation with the number of firms. An escalation in electricity accessibility is anticipated to result in a rise in the count of operating firms. Consequently, this is expected to elevate the demand for labor, stimulate economic growth, and concurrently alleviate unemployment.
  • Policymakers should actively promote and back both small and medium-scale enterprises, along with large corporations. This is evident in the strong correlation observed between the adult population and the overall business density rate, as well as the broader unemployment rate. As the population grows, businesses play a crucial role in generating employment opportunities for the expanding workforce.